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. 2021 Sep:24:101246.
doi: 10.1016/j.genrep.2021.101246. Epub 2021 Jun 11.

A bioinformatics approach for identifying potential molecular mechanisms and key genes involved in COVID-19 associated cardiac remodeling

Affiliations

A bioinformatics approach for identifying potential molecular mechanisms and key genes involved in COVID-19 associated cardiac remodeling

Hamid Ceylan. Gene Rep. 2021 Sep.

Abstract

In 2019 coronavirus disease (COVID-19), whose main complication is respiratory involvement, different organs may also be affected in severe cases. However, COVID-19 associated cardiovascular manifestations are limited at present. The main purpose of this study was to identify potential candidate genes involved in COVID-19-associated heart damage by bioinformatics analysis. Differently expressed genes (DEGs) were identified using transcriptome profiles (GSE150392 and GSE4172) downloaded from the GEO database. After gene and pathway enrichment analyses, PPI network visualization, module analyses, and hub gene extraction were performed using Cytoscape software. A total of 228 (136 up and 92 downregulated) overlapping DEGs were identified at these two microarray datasets. Finally, the top hub genes (FGF2, JUN, TLR4, and VEGFA) were screened out as the critical genes among the DEGs from the PPI network. Identification of critical genes and mechanisms in any disease can lead us to better diagnosis and targeted therapy. Our findings identified core genes shared by inflammatory cardiomyopathy and SARS-CoV-2. The findings of the current study support the idea that these key genes can be used in understanding and managing the long-term cardiovascular effects of COVID-19.

Keywords: ACE2, angiotensin-converting enzyme 2; Bioinformatics analysis; COVID-19; COVID-19, the coronavirus disease 2019; Cardiac remodeling; DEGs, differentially expressed genes; Differential expression; GEO, Gene Expression Omnibus; GO, Gene Ontology; KEGG, Kyoto Encyclopedia of Genes and Genome; PPI, the protein-protein interaction; SARS-CoV-2, severe acute respiratory syndrome coronavirus 2; STRING, the search tool for the retrieval of interacting genes.

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Conflict of interest statement

The author declares that there is no conflict of interest with any financial organization or corporation or individual that can inappropriately influence this work.

Figures

Fig. 1
Fig. 1
Identification of differentially expressed genes (DEGs) in the GSE150392 and GSE4172. a) Volcano plot of DEGs in the GSE150392 dataset (red represents upregulated genes with fold changes over 1.4 and green represents downregulated genes with fold changes less than 1.4.), b) volcano plot of DEGs in the GSE4172 dataset (red represents upregulated genes with fold changes over 1.4 and blue represents downregulated genes with fold changes less than 1.4.). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 2
Fig. 2
Venn diagram showing the overlapping DEGs between datasets.
Fig. 3
Fig. 3
GO analysis of overlapping DEGs. Red bars demonstrate genes of |log2FC| ≥ 0.5, blue bars represent genes of |log2FC| ≤ 0.5. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 4
Fig. 4
The whole protein-protein interaction (PPI) network of DEGs (red nodes represent upregulated DEGs and blue nodes represent downregulated DEGs). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 5
Fig. 5
Module analysis of PPI network. a) Module 1, b) Module 2 (red nodes represent upregulated DEGs and blue nodes represent downregulated DEGs). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)
Fig. 6
Fig. 6
KEGG pathway analysis of two significant modules in PPI.
Fig. 7
Fig. 7
Venn diagram of the intersecting genes derived using five algorithms. MCC: Maximal Clique Centrality, MNC: Maximum Neighborhood Component, EPC: Edge Percolated Component.

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